基于TDOA移动定位中的约束加权最小二乘算法

Constrained Weighted Least Squares Algorithms for Time Difference of Arrival-based Mobile Location

自 E -911定位需求颁布以来 ,移动台定位技术在国内外受到了高度的重视和深入研究。本文主要对无线定位中基于 TDOA的一种约束加权最小二乘算法进行了研究。该算法通过引用一个中间变量重组非线性方程组为线性方程组 ,然后利用加权最小二乘算法对该方程组进行求解 ,得到移动台的第一次位置估计值 ,根据得到的估计位置以及他们之间的内在联系 ,并引入拉格朗日乘数因子重新建立一个方程来对第一次估计进行修正 ,求解出符合条件的拉格朗日乘数因子 ,从而得到第二次位置估计值。仿真结果表明在一定的噪声环境中约束加权最小二乘算法能够达到克拉美罗下限 ,取得了较好的定位效果。

In this paper, we investigate the Constrained Weighted Least Squares(CWLS) algorithms for Time Difference of Arrival (TDOA) based mobile user location in wireless communication systems. The algorithms, which reorganizes nonlinear equations to linear equations via introduction of an intermediate variable and use weighted least squares algorithms, yields the first location estimator. According to the first location estimator and their inherent connection, using Lagrange gene the algorithms reconstruct a equation which correct the first location estimator. After finding out the coincident Lagrange gene, the second location estimator will be obtained. Simulation results demonstrate that the CWLS estimator achieves the CramérRao lower bound at sufficiently high signaltonoise conditions.